Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

Leisure sedentary behaviours are associated with increased risk of cardiovascular disease, but whether this relationship is causal is unknown. The aim of this study is to identify genetic determinants associated with leisure sedentary behaviours and to estimate the potential causal effect on coronary artery disease (CAD). Genome wide association analyses of leisure television watching, leisure computer use and driving behaviour in the UK Biobank identify 145, 36 and 4 genetic loci (P < 1×10-8), respectively. High genetic correlations are observed between sedentary behaviours and neurological traits, including education and body mass index (BMI). Two-sample Mendelian randomization (MR) analysis estimates a causal effect between 1.5 hour increase in television watching and CAD (OR 1.44, 95%CI 1.25-1.66, P = 5.63 × 10-07), that is partially independent of education and BMI in multivariable MR analyses. This study finds independent observational and genetic support for the hypothesis that increased sedentary behaviour by leisure television watching is a risk factor for CAD.

Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci

Genome-wide association studies (GWAS) have revealed thousands of genetic loci that underpin the complex biology of many human traits. However, the strength of GWAS - the ability to detect genetic association by linkage disequilibrium (LD) - is also its limitation. Whilst the ever-increasing study size and improved design have augmented the power of GWAS to detect effects, differentiation of causal variants or genes from other highly correlated genes associated by LD remains the real challenge. This has severely hindered the biological insights and clinical translation of GWAS findings. Although thousands of disease susceptibility loci have been reported, causal genes at these loci remain elusive. Machine learning (ML) techniques offer an opportunity to dissect the heterogeneity of variant and gene signals in the post-GWAS analysis phase. ML models for GWAS prioritization vary greatly in their complexity, ranging from relatively simple logistic regression approaches to more complex ensemble models such as random forests and gradient boosting, as well as deep learning models, i.e., neural networks. Paired with functional validation, these methods show important promise for clinical translation, providing a strong evidence-based approach to direct post-GWAS research. However, as ML approaches continue to evolve to meet the challenge of causal gene identification, a critical assessment of the underlying methodologies and their applicability to the GWAS prioritization problem is needed. This review investigates the landscape of ML applications in three parts: selected models, input features, and output model performance, with a focus on prioritizations of complex disease associated loci. Overall, we explore the contributions ML has made towards reaching the GWAS end-game with consequent wide-ranging translational impact.

Development and Validation of a Medication Selection Model Under Clinical Application of Renin-Angiotensin Inhibitor Combined with Calcium Channel Blocker for Hypertension Patients

Background

This study evaluated the impact of clinical features and concomitant conditions on the clinical selection of different renin-angiotensin system (RAS) inhibitors in patients with hypertension, and built a renin-angiotensin inhibitors selection model (RAISM) to provide a reference for clinical decision making.

Material/Methods

We included 213 hypertensive patients in the study cohort; patients were divided into two groups: the angiotensin-converting enzyme inhibitor (ACEI) combined with calcium channel blocker (CCB) group (ACEI+CCB group) and the angiotensin receptor antagonist (ARB) combined with CCB group (ARB+CCB group). Basic demographic characteristics and concomitant conditions of the patients were compared. Single-factor and multi-factor analysis was performed by adopting logistic regression model. The RAISM was established by utilizing the nomograph technology. C-index and calibration curve were used to evaluate the model’s efficacy.

Results

In the study, 34.27% of the patients used ACEI+CCB and 65.73% of patients used ARB+CCB. The difference in age, body mass index (BMI), elderly patient, diabetes, renal dysfunction, and hyperlipidemia between the 2 groups determined medication selection. To be specific, compared to the group using ARB+CCB, the odds ratios and 95% confidence interval (CI) of the aforementioned factors for the ACEI+CCB group were 0.476 (0.319–0.711), 1.274 (1.001–1.622), 0.365 (0.180–0.743), 0.471 (0.203–1.092), 0.542 (0.268–1.094), and 0.270 (0.100–0.728), respectively; The C-index of RAISM acquired from the model construction parameters was 0.699, and the correction curve demonstrated that the model has good discriminative ability.

Conclusions

The outcome of our study suggests that independent discriminating factors that influence the clinical selection of different RAS inhibitors were elderly patient, renal insufficiency, and hyperlipidemia; and the RAISM constructed in this study has good predictability and clinical benefit.

Significance of sphingosine-1-phosphate in cardiovascular physiology and pathology

Sphingosine-1-phosphate (S1P) is a signaling lipid, synthetized by sphingosine kinases (SPHK1 and SPHK2), that affects cardiovascular function in various ways. S1P signaling is complex, particularly since its molecular action is reliant on the differential expression of its receptors (S1PR1, S1PR2, S1PR3, S1PR4, S1PR5) within various tissues. Significance of this sphingolipid is manifested early in vertebrate development as certain defects in S1P signaling result in embryonic lethality due to defective vasculo- or cardiogenesis. Similar in the mature organism, S1P orchestrates both physiological and pathological processes occurring in the heart and vasculature of higher eukaryotes. S1P regulates cell fate, vascular tone, endothelial function and integrity as well as lymphocyte trafficking, thus disbalance in its production and signaling has been linked with development of such pathologies as arterial hypertension, atherosclerosis, endothelial dysfunction and aberrant angiogenesis. Number of signaling mechanisms are critical - from endothelial nitric oxide synthase through STAT3, MAPK and Akt pathways to HDL particles involved in redox and inflammatory balance. Moreover, S1P controls both acute cardiac responses (cardiac inotropy and chronotropy), as well as chronic processes (such as apoptosis and hypertrophy), hence numerous studies demonstrate significance of S1P in the pathogenesis of hypertrophic/fibrotic heart disease, myocardial infarction and heart failure. This review presents current knowledge concerning the role of S1P in the cardiovascular system, as well as potential therapeutic approaches to target S1P signaling in cardiovascular diseases.

White Blood Cells and Blood Pressure: A Mendelian Randomization Study

BACKGROUND

High blood pressure (BP) is a risk factor for cardiovascular morbidity and mortality. While BP is regulated by the function of kidney, vasculature, and sympathetic nervous system, recent experimental data suggest that immune cells may play a role in hypertension.

METHODS

We studied the relationship between major white blood cell types and blood pressure in the UK Biobank population and used Mendelian randomization (MR) analyses using the ≈750 000 UK-Biobank/International Consortium of Blood Pressure-Genome-Wide Association Studies to examine which leukocyte populations may be causally linked to BP.

RESULTS

A positive association between quintiles of lymphocyte, monocyte, and neutrophil counts, and increased systolic BP, diastolic BP, and pulse pressure was observed (eg, adjusted systolic BP mean±SE for 1st versus 5th quintile respectively: 140.13±0.08 versus 141.62±0.07 mm Hg for lymphocyte, 139.51±0.08 versus 141.84±0.07 mm Hg for monocyte, and 137.96±0.08 versus 142.71±0.07 mm Hg for neutrophil counts; all P<10^-50). Using 121 single nucleotide polymorphisms in MR, implemented through the inverse-variance weighted approach, we identified a potential causal relationship of lymphocyte count with systolic BP and diastolic BP (causal estimates: 0.69 [95% CI, 0.19-1.20] and 0.56 [95% CI, 0.23-0.90] of mm Hg per 1 SD genetically elevated lymphocyte count, respectively), which was directionally concordant to the observational findings. These inverse-variance weighted estimates were consistent with other robust MR methods. The exclusion of rs3184504 SNP in the SH2B3 locus attenuated the magnitude of the signal in some of the MR analyses. MR in the reverse direction found evidence of positive effects of BP indices on counts of monocytes, neutrophils, and eosinophils but not lymphocytes or basophils. Subsequent MR testing of lymphocyte count in the context of genetic correlation with renal function or resting and postexercise heart rate demonstrated a positive association of lymphocyte count with urine albumin-to-creatinine ratio.

CONCLUSIONS

Observational and genetic analyses demonstrate a concordant, positive and potentially causal relationship of lymphocyte count with systolic BP and diastolic BP.

Genomics of Blood Pressure and Hypertension: Extending the Mosaic Theory Toward Stratification

The genetic architecture of blood pressure (BP) now includes more than 30 genes, with rare mutations resulting in inherited forms of hypertension or hypotension, and 1477 common single-nucleotide polymorphisms (SNPs). These signify the heterogeneity of the BP phenotype and support the mosaic theory of hypertension. The majority of monogenic syndromes involve the renin-angiotensin-aldosterone system and the adrenal glucocorticoid pathway, and a smaller fraction are due to rare neuroendocrine tumours of the adrenal glands and the sympathetic and parasympathetic paraganglia. Somatic mutations in genes coding for ion channels (KCNJ5 and CACNA1D) and adenosine triphosphatases (ATP1A1 and ATP2B3) highlight the central role of calcium signalling in autonomous aldosterone production by the adrenal gland. The per-SNP BP effect is small for SNPs according to genome-wide association studies (GWAS), and all of the GWAS-identified BP SNPs explain ∼ 27% of the 30%-50% estimated heritability of BP. Uromodulin is a novel pathway identified by GWAS, and it has now progressed to a genotype-directed clinical trial. The majority of the GWAS-identified BP SNPs show pleiotropic associations, and unravelling those signals and underpinning biological pathways offers potential opportunities for drug repurposing. The GWAS signals are predominantly from Europe-centric studies with other ancestries underrepresented, however, limiting the generalisability of the findings. In this review, we leverage the burgeoning list of polygenic and monogenic variants associated with BP regulation along with phenome-wide studies in the context of the mosaic theory of hypertension, and we explore potential translational aspects that underlie different hypertension subtypes.

Modularity/non-cumulativity of quantitative trait loci on blood pressure

Large numbers of quantitative trait loci (QTLs) for blood pressure (BP) exist and have long been thought to function by accumulating their individual miniscule effects. Recent experimental evidence in the functional biology of BP control has tested this intuitive assumption. A new paradigm has emerged that BP is biologically determined in modularity by multiple QTLs. Functionally, when a master regulator is taken out, distinct epistatic modules organize biological 'blocks' into a genetic architecture, and serve as basic functional cores from which numerous QTLs act together to physiologically formulate BP. An epistatic module refers to the grouping of QTLs that perform their functions epistatically to one another and influence BP as a group. The modularity mechanism framework indicates that BP as a quantitatively-measured trait is not cumulatively determined and implies that the QTLs in the same epistatic module may participate in the same pathway leading to the BP control, and the QTLs from separate epistatic modules may act in divergent but parallel pathways. This mechanistic conceptualization and subsequent validations synergize with anticipated demands from current human epidemiological studies, since the outcome from them primarily implicates single nucleotide polymorphisms with unknown functions. Eventually, functional understandings of the human results have to be realized by their pathogenic directionality and mechanisms biologically controlling BP.

Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.

Genome-Wide Analysis Identifies Two Susceptibility Loci for Positive Thyroid Peroxidase and Thyroglobulin Antibodies

INTRODUCTION

Thyroid peroxidase (TPO) and thyroglobulin (Tg) are main components of the thyroid gland and play an essential role in thyroid hormone synthesis. The development of antibodies to thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) is the major diagnostic hallmark and early indicator of autoimmune thyroid disease. TPOAb and TgAb are under strong genetic influence; however, genetic factors that determine thyroid antibody positivity are largely unknown.

MATERIALS AND METHODS

To identify novel loci associated with TPOAb and/or TgAb positivity, we performed a genome-wide meta-analysis in a total of 2613 individuals from Croatia. Participants with elevated plasma TPOAb and/or TgAb were defined as cases (N = 619) and those with TPOAb and TgAb within reference values were defined as controls (N = 1994).

RESULTS

We identified 2 novel loci, of which 1 is located within the YES1 gene (rs77284350, P = 1.50 × 10-8), and the other resides within the IRF8 gene (rs16939945, P = 5.04 × 10-8).

CONCLUSIONS

Although the observed variants were associated with TPOAb and TgAb positivity for the first time, both YES1 and IRF8 were previously linked to susceptibility to other autoimmune diseases, and represent plausible biological candidates. This study adds to the knowledge of genetics underlying thyroid antibodies and provides a good basis for further research.

Carotid Intima-Media Thickness: Novel Loci, Sex-Specific Effects, and Genetic Correlations With Obesity and Glucometabolic Traits in UK Biobank

OBJECTIVE

Atherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultrasound measurement of the carotid intima-media thickness (cIMT) can be used to measure vascular remodeling, which is indicative of atherosclerosis. Genome-wide association studies have identified many genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here, we conducted genome-wide association analyses in UKB (UK Biobank; N=22 179), the largest single study with consistent cIMT measurements. Approach and Results: We used BOLT-LMM software to run linear regression of cIMT in UKB, adjusted for age, sex, and genotyping chip. In white British participants, we identified 5 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a locus on chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body mass index and glucometabolic traits were also observed. Two loci influenced risk of ischemic heart disease.

CONCLUSIONS

These findings replicate previously reported associations, highlight novel biology, and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

Variable prediction accuracy of polygenic scores within an ancestry group

Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group (i.e., when there are negligible differences in linkage disequilibrium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on characteristics such as the socio-economic status, age or sex of the individuals in which the GWAS and the prediction were conducted, as well as on the GWAS design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.

Variable prediction accuracy of polygenic scores within an ancestry group

Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group (i.e., when there are negligible differences in linkage disequilibrium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on characteristics such as the socio-economic status, age or sex of the individuals in which the GWAS and the prediction were conducted, as well as on the GWAS design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.

Temporal Expression and Cellular Localization of PAPPA2 in the Developing Kidney of Rat

PAPPA2 is a metalloproteinase which cleaves insulin-like growth factor binding protein (IGFBP)-3 and IGFBP-5, and its role in pregnancy and postnatal growth is primarily studied. Using exclusion mapping, we reported a subcongenic (26-P) rat where a 0.71-Mbp region containing the pregnancy-associated plasma protein a2 (Pappa2) allele of salt-insensitive Brown Norway (BN) was introgressed into Dahl saltsensitive (SS) genetic background, resulting in the reduction of salt sensitivity. Pappa2 was differentially expressed in the adult kidney of 26-P and SS rats. Here, the expression and cellular localization of Pappa2 in embryonic and postnatal kidneys of 26-P and SS rats were examined. Pappa2 mRNA expression was 5-fold higher in the embryonic kidney (day 20.5) of the 26-P rat compared with the SS rat. Pappa2 mRNA expression progressively increased with the development of kidney, reaching a peak at postnatal day 5 before trending downward in subsequent stages of development in both strains. At all tested time points, Pappa2 remained higher in the 26-P compared with the SS rat kidney. Immunohistochemistry studies localized PAPPA2 in the ureteric bud (UB) and distal part of S-shaped body. PAPPA2 was colocalized with IGFBP-5 in the UB and Na⁺/K⁺/2Cl^- cotransporter-stained tubules, respectively. Future studies are needed to determine the role of Pappa2 in kidney development and mechanistic pathways involved in this process.

Artificial Intelligence for Cardiac Imaging-Genetics Research

Cardiovascular conditions remain the leading cause of mortality and morbidity worldwide, with genotype being a significant influence on disease risk. Cardiac imaging-genetics aims to identify and characterize the genetic variants that influence functional, physiological, and anatomical phenotypes derived from cardiovascular imaging. High-throughput DNA sequencing and genotyping have greatly accelerated genetic discovery, making variant interpretation one of the key challenges in contemporary clinical genetics. Heterogeneous, low-fidelity phenotyping and difficulties integrating and then analyzing large-scale genetic, imaging and clinical datasets using traditional statistical approaches have impeded process. Artificial intelligence (AI) methods, such as deep learning, are particularly suited to tackle the challenges of scalability and high dimensionality of data and show promise in the field of cardiac imaging-genetics. Here we review the current state of AI as applied to imaging-genetics research and discuss outstanding methodological challenges, as the field moves from pilot studies to mainstream applications, from one dimensional global descriptors to high-resolution models of whole-organ shape and function, from univariate to multivariate analysis and from candidate gene to genome-wide approaches. Finally, we consider the future directions and prospects of AI imaging-genetics for ultimately helping understand the genetic and environmental underpinnings of cardiovascular health and disease.

Identification of Circulating Proteins Associated With Blood Pressure Using Mendelian Randomization

BACKGROUND

Hypertension is a common modifiable risk factor for cardiovascular disease and mortality. Pathophysiological mechanisms leading to hypertension remain incompletely understood. Mendelian randomization (MR) allows the evaluation of the causal role of markers by minimizing the risk of biases such as reverse causation and confounding. We aimed to identify novel circulating proteins associated with blood pressure through a comprehensive screen of 227 blood biomarkers using MR.

METHODS

Genetic determinants of 227 biomarkers were identified in ORIGIN (Outcome Reduction With Initial Glargine Intervention; URL: http://www.clinicaltrials.gov. Unique identifier: NCT00069784) participants (N=4147) and combined with genetic effects on systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure from the International Consortium for Blood Pressure (74 064 individuals) using MR. Results were replicated in the UK Biobank (up to 319 103 individuals) and using another biomarker dataset (N=3301). MR analyses with cardiovascular risk factors and outcomes as well as other biomarkers were performed to further evaluate the mechanisms involved.

RESULTS

Six biomarkers were associated with blood pressure using MR after adjustment for multiple hypothesis testing. Relationships between NT-proBNP (N-terminal Pro-B-type natriuretic peptide), systolic blood pressure, and diastolic blood pressure confirmed previous reports. Novel circulating proteins associated with blood pressure were also identified. uPA (urokinase-type plasminogen activator) was related to systolic blood pressure; ADM (adrenomedullin) was related to systolic blood pressure and pulse pressure; IL (interleukin) 16 was related to diastolic blood pressure; cFn (cellular fibronectin) and IGFBP3 (insulin-like growth factor-binding protein 3) were related to pulse pressure. With the exception of IL16 and diastolic blood pressure (P=0.58), these relationships were validated in the UK Biobank (P<0.0001). Further MR analyses with cardiovascular risk factors and outcomes showed relationships between NT-proBNP and large-artery atherosclerotic stroke, IGFBP3 and diabetes mellitus as well as cFn and body mass index.

CONCLUSIONS

We identified novel biomarkers associated with blood pressure using MR. These markers could prove useful for risk assessment and as potential therapeutic targets.

Comparative and Functional Genomic Resource for Mechanistic Studies of Human Blood Pressure-Associated Single Nucleotide Polymorphisms

The objective of the current study is to use comparative and functional genomic analysis to help to understand the biological mechanism mediating the effect of single nucleotide polymorphisms (SNPs) on blood pressure. We mapped 26 585 SNPs that are in linkage disequilibrium with 1071 human blood pressure-associated sentinel SNPs to 9447 syntenic regions in the mouse genome. Approximately 21.8% of the 1071 linkage disequilibrium regions are located at least 10 kb from any protein-coding gene. Approximately 300 blood pressure-associated SNPs are expression quantitative trait loci for a few dozen known blood pressure physiology genes in tissues including specific kidney regions. Blood pressure-associated sentinel SNPs are significantly enriched for expression quantitative trait loci for blood pressure physiology genes compared with randomly selected SNPs (P<0.00023, Fisher exact test). Using a newly developed deep learning method and other methods, we identified SNPs that were predicted to influence the conservation of CTCF (CCCTC-binding factor) binding across cell types, transcription factor binding, mRNA splicing, or secondary structures of RNA including long noncoding RNA. The SNPs were more likely to be located in CTCF-binding regions than what would be expected from the whole genome (P=4.90×10^-7, Pearson χ² test). One example synonymous SNP rs9337951 was predicted to influence the secondary structure of its host mRNA JCAD (junctional cadherin 5 associated) and was experimentally validated to influence JCAD protein expression. These findings provide an extensive comparative and functional genomic resource for developing experiments to test the functional significance of human blood pressure-associated SNPs in human cells and animal models.

Glucose-Dependent Insulinotropic Polypeptide Receptor Therapies for the Treatment of Obesity, Do Agonists = Antagonists?

Glucose-dependent insulinotropic polypeptide receptor (GIPR) is associated with obesity in human genome-wide association studies. Similarly, mouse genetic studies indicate that loss of function alleles and glucose-dependent insulinotropic polypeptide overexpression both protect from high-fat diet-induced weight gain. Together, these data provide compelling evidence to develop therapies targeting GIPR for the treatment of obesity. Further, both antagonists and agonists alone prevent weight gain, but result in remarkable weight loss when codosed or molecularly combined with glucagon-like peptide-1 analogs preclinically. Here, we review the current literature on GIPR, including biology, human and mouse genetics, and pharmacology of both agonists and antagonists, discussing the similarities and differences between the 2 approaches. Despite opposite approaches being investigated preclinically and clinically, there may be viability of both agonists and antagonists for the treatment of obesity, and we expect this area to continue to evolve with new clinical data and molecular and pharmacological analyses of GIPR function.

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.

Ordered multinomial regression for genetic association analysis of ordinal phenotypes at Biobank scale

Logistic regression is the primary analysis tool for binary traits in genome-wide association studies (GWAS). Multinomial regression extends logistic regression to multiple categories. However, many phenotypes more naturally take ordered, discrete values. Examples include (a) subtypes defined from multiple sources of clinical information and (b) derived phenotypes generated by specific phenotyping algorithms for electronic health records (EHR). GWAS of ordinal traits have been problematic. Dichotomizing can lead to a range of arbitrary cutoff values, generating inconsistent, hard to interpret results. Using multinomial regression ignores trait value hierarchy and potentially loses power. Treating ordinal data as quantitative can lead to misleading inference. To address these issues, we analyze ordinal traits with an ordered, multinomial model. This approach increases power and leads to more interpretable results. We derive efficient algorithms for computing test statistics, making ordinal trait GWAS computationally practical for Biobank scale data. Our method is available as a Julia package OrdinalGWAS.jl. Application to a COPDGene study confirms previously found signals based on binary case-control status, but with more significance. Additionally, we demonstrate the capability of our package to run on UK Biobank data by analyzing hypertension as an ordinal trait.

Identifying cross-disease components of genetic risk across hospital data in the UK Biobank

Genetic risk factors frequently affect multiple common human diseases, providing insight into shared pathophysiological pathways and opportunities for therapeutic development. However, systematic identification of genetic profiles of disease risk is limited by the availability of both comprehensive clinical data on population-scale cohorts and the lack of suitable statistical methodology that can handle the scale of and differential power inherent in multi-phenotype data. Here, we develop a disease-agnostic approach to cluster genetic risk profiles for 3,025 genome-wide independent loci across 19,155 disease classification codes from 320,644 participants in the UK Biobank, representing a large and heterogeneous population. We identify 339 distinct disease association profiles and use multiple approaches to link clusters to underlying biological pathways. We show how clusters can decompose the variance and covariance in risk for disease, thereby identifying underlying biological processes and their impact. We demonstrate the use of clusters in defining disease relationships and their potential in informing therapeutic strategies.

Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but their predictive power has been modest compared to established stroke risk factors. Here, using a meta-scoring approach, we develop a metaGRS for ischaemic stroke (IS) and analyse this score in the UK Biobank (n = 395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22-1.31 per metaGRS standard deviation) doubles that of a previous GRS, identifying a subset of individuals at monogenic levels of risk: the top 0.25% of metaGRS have three-fold risk of IS. The metaGRS is similarly or more predictive compared to several risk factors, such as family history, blood pressure, body mass index, and smoking. We estimate the reductions needed in modifiable risk factors for individuals with different levels of genomic risk and suggest that, for individuals with high metaGRS, achieving risk factor levels recommended by current guidelines may be insufficient to mitigate risk.

Pharmacogenomics And Hypertension: Current Insights

Hypertension is a multifactorial disease that affects approximately one billion subjects worldwide and is a major risk factor associated with cardiovascular events, including coronary heart disease and cerebrovascular accidents. Therefore, adequate blood pressure control is important to prevent these events, reducing premature mortality and disability. However, only one third of patients have the effective control of blood pressure, despite several classes of antihypertensive drugs available. These disappointing outcomes may be at least in part explained by interpatient variability in drug response due to genetic polymorphisms. To address the effects of genetic polymorphisms on blood pressure responses to the antihypertensive drug classes, studies have applied candidate genes and genome wide approaches. More recently, a third approach that considers gene-gene interactions has also been applied in hypertension pharmacogenomics. In this article, we carried out a comprehensive review of recent findings on the pharmacogenomics of antihypertensive drugs, including diuretics, β-blockers, angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, and calcium channel blockers. We also discuss the limitations and inconsistences that have been found in hypertension pharmacogenomics and the challenges to implement this valuable approach in clinical practice.

Over 1000 genetic loci influencing blood pressure with multiple systems and tissues implicated

High blood pressure (BP) remains the major heritable and modifiable risk factor for cardiovascular disease. Persistent high BP, or hypertension, is a complex trait with both genetic and environmental interactions. Despite swift advances in genomics, translating new discoveries to further our understanding of the underlying molecular mechanisms remains a challenge. More than 500 loci implicated in the regulation of BP have been revealed by genome-wide association studies (GWAS) in 2018 alone, taking the total number of BP genetic loci to over 1000. Even with the large number of loci now associated to BP, the genetic variance explained by all loci together remains low (~5.7%). These genetic associations have elucidated mechanisms and pathways regulating BP, highlighting potential new therapeutic and drug repurposing targets. A large proportion of the BP loci were discovered and reported simultaneously by multiple research groups, creating a knowledge gap, where the reported loci to date have not been investigated in a harmonious way. Here, we review the BP-associated genetic variants reported across GWAS studies and investigate their potential impact on the biological systems using in silico enrichment analyses for pathways, tissues, gene ontology and genetic pleiotropy.

Genome Wide Analysis Approach Suggests Chromosome 2 Locus to be Associated with Thiazide and Thiazide Like-Diuretics Blood Pressure Response

Chlorthalidone (CTD) is more potent than hydrochlorothiazide (HCTZ) in reducing blood pressure (BP) in hypertensive patients, though both are plagued with BP response variability. However, there is a void in the literature regarding the genetic determinants contributing to the variability observed in BP response to CTD. We performed a discovery genome wide association analysis of BP response post CTD treatment in African Americans (AA) and European Americans (EA) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and replication in an independent cohort of AA and EA treated with HCTZ from the PEAR study, followed by a race specific meta-analysis of the two studies. Successfully replicated SNPs were further validated in beta-blocker treated participants from PEAR-2 and PEAR for opposite direction of association. The replicated and validated signals were further evaluated by protein-protein interaction network analysis. An intronic SNP rs79237970 in the WDR92 (eQTL for PPP3R1) was significantly associated with better DBP response to CTD (p = 5.76 × 10-6, β = -15.75) in the AA cohort. This SNP further replicated in PEAR (p = 0.00046, β = -9.815) with a genome wide significant meta-analysis p-value of 8.49 × 10-9. This variant was further validated for opposite association in two β-blockers treated cohorts from PEAR-2 metoprolol (p = 9.9 × 10-3, β = 7.47) and PEAR atenolol (p = 0.04, β = 4.36) for association with DBP. Studies have implicated WDR92 in coronary artery damage. PPP3R1 is the regulatory subunit of the calcineurin complex. Use of calcineurin inhibitors is associated with HTN. Studies have also shown polymorphisms in PPP3R1 to be associated with ventricular hypertrophy in AA hypertensive patients. Protein-protein interaction analysis further identified important hypertension related pathways such as inositol phosphate-mediated signaling and calcineurin-NFAT signaling cascade as important biological process associated with PPP3R1 which further strengthen the potential importance of this signal. These data collectively suggest that WDR92 and PPP3R1 are novel candidates that may help explain the genetic underpinnings of BP response of thiazide and thiazide-like diuretics and help identify the patients better suited for thiazide and thiazide-like diuretics compared to β-blockers for improved BP management. This may further help advance personalized approaches to antihypertensive therapy.

Powerful rare variant association testing in a copula-based joint analysis of multiple phenotypes

In genetic association studies of rare variants, the low power of association tests is one of the main challenges. In this study, we propose a new single-marker association test called C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes), which is based on a joint model of multiple phenotypes given genetic markers and other covariates. We evaluated its performance and compared its empirical type I error and power with existing univariate and multivariate single-marker and multi-marker rare-variant tests in extensive simulation studies. C-JAMP yielded unbiased genetic effect estimates and valid type I errors with an adjusted test statistic. When strongly dependent traits were jointly analyzed, C-JAMP had the highest power in all scenarios except when a high percentage of variants were causal with moderate/small effect sizes. When traits with weak or moderate dependence were analyzed, whether C-JAMP or competing approaches had higher power depended on the effect size. When C-JAMP was applied with a misspecified copula function, it still achieved high power in some of the scenarios considered. In a real-data application, we analyzed sequencing data using C-JAMP and performed the first genome-wide association studies of high-molecular-weight and medium-molecular-weight adiponectin plasma concentrations. C-JAMP identified 20 rare variants with p-values smaller than 10^-5 , while all other tests resulted in the identification of fewer variants with higher p-values. In summary, the results indicate that C-JAMP is a powerful, flexible, and robust method for association studies, and we identified novel candidate markers for adiponectin. C-JAMP is implemented as an R package and freely available from https://cran.r-project.org/package=CJAMP.

Unraveling Difficult Answers: From Genotype to Phenotype in Coronary Artery Disease

Genome-wide association studies (GWASs) have robustly found a correlation between coronary artery disease (CAD) and an intergenic region at locus 9p21.3. However, the mechanistic implication of this association is unknown. Recently in Cell, Lo Sardo et al. used hiPSC genome editing to demonstrate how this locus contributes to CAD predisposition.

Causal association between periodontitis and hypertension: evidence from Mendelian randomization and a randomized controlled trial of non-surgical periodontal therapy

AIMS

Inflammation is an important driver of hypertension. Periodontitis is a chronic inflammatory disease, which could provide a mechanism for pro-hypertensive immune activation, but evidence of a causal relationship in humans is scarce. We aimed to investigate the nature of the association between periodontitis and hypertension.

METHODS AND RESULTS

We performed a two-sample Mendelian randomization analysis in the ∼750 000 UK-Biobank/International Consortium of Blood Pressure-Genome-Wide Association Studies participants using single nucleotide polymorphisms (SNPs) in SIGLEC5, DEFA1A3, MTND1P5, and LOC107984137 loci GWAS-linked to periodontitis, to ascertain their effect on blood pressure (BP) estimates. This demonstrated a significant relationship between periodontitis-linked SNPs and BP phenotypes. We then performed a randomized intervention trial on the effects of treatment of periodontitis on BP. One hundred and one hypertensive patients with moderate/severe periodontitis were randomized to intensive periodontal treatment (IPT; sub- and supragingival scaling/chlorhexidine; n = 50) or control periodontal treatment (CPT; supragingival scaling; n = 51) with mean ambulatory 24-h (ABPM) systolic BP (SBP) as primary outcome. Intensive periodontal treatment improved periodontal status at 2 months, compared to CPT. This was accompanied by a substantial reduction in mean SBP in IPT compared to the CPT (mean difference of -11.1 mmHg; 95% CI 6.5-15.8; P < 0.001). Systolic BP reduction was correlated to periodontal status improvement. Diastolic BP and endothelial function (flow-mediated dilatation) were also improved by IPT. These cardiovascular changes were accompanied by reductions in circulating IFN-γ and IL-6 as well as activated (CD38+) and immunosenescent (CD57+CD28null) CD8+T cells, previously implicated in hypertension.

CONCLUSION

A causal relationship between periodontitis and BP was observed providing proof of concept for development of clinical trial in a large cohort of hypertensive patients. ClinicalTrials.gov: NCT02131922.

Identification of Phosphorylation Associated SNPs for Blood Pressure, Coronary Artery Disease and Stroke from Genome-wide Association Studies

PURPOSE

Phosphorylation-related SNP (phosSNP) is a non-synonymous SNP that might influence protein phosphorylation status. The aim of this study was to assess the effect of phosSNPs on blood pressure (BP), coronary artery disease (CAD) and ischemic stroke (IS).

METHODS

We examined the association of phosSNPs with BP, CAD and IS in shared data from genome-wide association studies (GWAS) and tested if the disease loci were enriched with phosSNPs. Furthermore, we performed quantitative trait locus analysis to find out if the identified phosSNPs have impacts on gene expression, protein and metabolite levels.

RESULTS

We found numerous phosSNPs for systolic BP (count=148), diastolic BP (count=206), CAD (count=20) and IS (count=4). The most significant phosSNPs for SBP, DBP, CAD and IS were rs1801131 in MTHFR, rs3184504 in SH2B3, rs35212307 in WDR12 and rs3184504 in SH2B3, respectively. Our analyses revealed that the associated SNPs identified by the original GWAS were significantly enriched with phosSNPs and many well-known genes predisposing to cardiovascular diseases contain significant phosSNPs. We found that BP, CAD and IS shared for phosSNPs in loci that contain functional genes involve in cardiovascular diseases, e.g., rs11556924 (ZC3HC1), rs1971819 (ICA1L), rs3184504 (SH2B3), rs3739998 (JCAD), rs903160 (SMG6). Four phosSNPs in ADAMTS7 were significantly associated with CAD, including the known functional SNP rs3825807. Moreover, the identified phosSNPs seemed to have the potential to affect transcription regulation and serum levels of numerous cardiovascular diseases-related proteins and metabolites.

CONCLUSION

The findings suggested that phosSNPs may play important roles in BP regulation and the pathological mechanisms of CAD and IS.

A genome-wide association and replication study of blood pressure in Ugandan early adolescents

BACKGROUND

Genetic association studies of blood pressure (BP) have mostly been conducted in non-African populations. Using the Entebbe Mother and Baby Study (EMaBS), we aimed to identify genetic variants associated with BP among Ugandan adolescents.

METHODS

Systolic and diastolic BP were measured among 10- and 11-year olds. Whole-genome genotype data were generated using Illumina omni 2.5M arrays and untyped variants were imputed. Genome-wide association study (GWAS) was conducted using linear mixed model regression to account for population structure. Linear regression analysis was used to assess whether variants previously associated with BP (p < 5.0 × 10-8 ) in published BP GWASs were replicated in our study.

RESULTS

Of the 14 million variants analyzed among 815 adolescents, none reached genome-wide significance (p < 5.0×10-8 ) for association with systolic or diastolic BP. The most strongly associated variants were rs181430167 (p = 6.8 × 10-7 ) for systolic BP and rs12991132 (p = 4.0 × 10-7 ) for diastolic BP. Thirty-three (17 single nucleotide polymorphisms (SNPs) for systolic BP, 15 SNPs for diastolic BP and one SNP for both) of 330 variants previously identified as associated with BP were replicated in this study, but none remained significant after accounting for multiple testing.

CONCLUSION

Variants showing suggestive associations are worthy of future investigation. Replication results suggest that variants influencing adolescent BP may overlap somewhat with those already established in previous studies, largely based on adults in Western settings.

Translational genomics and precision medicine: Moving from the lab to the clinic

Translational genomics aims to improve human health by building on discoveries made through genetics research and applying them in the clinical setting. This progress has been made possible by technological advances in genomics and analytics and by the digital revolution. Such advances should enable the development of prognostic markers, tailored interventions, and the design of prophylactic preventive approaches. We are at the cusp of predicting disease risk for some disorders by means of polygenic risk scores integrated with classical epidemiological risk factors. This should lead to better risk stratification and clinical decision-making. A deeper understanding of the link between genome-wide sequence and association with well-characterized phenotypes will empower the development of biomarkers to aid diagnosis, inform disease progression trajectories, and allow better targeting of treatments to those patients most likely to respond.

Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease

Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.

Differential expression of microRNAs in Alzheimer's disease brain, blood, and cerebrospinal fluid

INTRODUCTION

Several microRNAs (miRNAs) have been implicated in Alzheimer's disease pathogenesis, but the evidence from individual case-control studies remains inconclusive.

METHODS

A systematic literature review was performed, followed by standardized multistage data extraction, quality control, and meta-analyses on eligible data for brain, blood, and cerebrospinal fluid specimens. Results were compared with miRNAs reported in the abstracts of eligible studies or recent qualitative reviews to assess novelty.

RESULTS

Data from 147 independent data sets across 107 publications were quantitatively assessed in 461 meta-analyses. Twenty-five, five, and 32 miRNAs showed studywide significant differential expression (α < 1·08 × 10^-4) in brain, cerebrospinal fluid, and blood-derived specimens, respectively, with 5 miRNAs showing differential expression in both brain and blood. Of these 57 miRNAs, 13 had not been reported in the abstracts of previous original or review articles.

DISCUSSION

Our systematic assessment of differential miRNA expression is the first of its kind in Alzheimer's disease and highlights several miRNAs of potential relevance.

Genomic Association Analysis Reveals Variants Associated With Blood Pressure Response to Beta-Blockers in European Americans

European Americans (EA) have a better antihypertensive response to β-blockers when compared with African Americans, albeit with some variability. We undertook a genomewide association study to elucidate the underlying genetic determinants in EA contributing to this variability in blood pressure (BP) response. A discovery genomewide association study of change in BP post-metoprolol treatment was performed in EA participants (n = 201) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and tested for replication in the atenolol-treated EA from the PEAR study (n = 233). Rs294610 in the FGD5, which encodes for FYVE, RhoGEF and PH Domain Containing 5, (expression quantitative trait loci for FGD5 in the small intestine) was significantly associated with increased diastolic BP response to β-blockers in the PEAR-2 study (P = 3.41 × 10-6 , β = -2.70) and replicated (P = 0.01, β = -1.17) in the PEAR study. Post-meta-analysis of these studies, an additional single nucleotide polymorphism rs45545233 in the SLC4A1, encoding for Solute Carrier Family 4 Member 1, (expression quantitative trait loci for dual specificity phosphatase 3 in the artery tibial) was identified that was significantly associated with a poor response to β-blockers (P = 3.43 × 10-6 , β = 4.57) and was replicated in the atenolol add-on cohort (P = 0.007, β = 4.97). We identified variants in FGD5 and SLC4A1, which have been previously cited as candidate genes for hypertension, to be associated with a β-blocker BP response in EA. Further elucidation is warranted of the underlying mechanisms of these variants and genes by which they influence the BP response to β-blockers.

New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders

Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d-1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.

The Older Finnish Twin Cohort - 45 Years of Follow-up

The older Finnish Twin Cohort (FTC) was established in 1974. The baseline survey was in 1975, with two follow-up health surveys in 1981 and 1990. The fourth wave of assessments was done in three parts, with a questionnaire study of twins born during 1945-1957 in 2011-2012, while older twins were interviewed and screened for dementia in two time periods, between 1999 and 2007 for twins born before 1938 and between 2013 and 2017 for twins born in 1938-1944. The content of these wave 4 assessments is described and some initial results are described. In addition, we have invited twin-pairs, based on response to the cohortwide surveys, to participate in detailed in-person studies; these are described briefly together with key results. We also review other projects based on the older FTC and provide information on the biobanking of biosamples and related phenotypes.

GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits

Urinary sodium and potassium excretion are associated with blood pressure (BP) and cardiovascular disease (CVD). The exact biological link between these traits is yet to be elucidated. Here, we identify 50 loci for sodium and 13 for potassium excretion in a large-scale genome-wide association study (GWAS) on urinary sodium and potassium excretion using data from 446,237 individuals of European descent from the UK Biobank study. We extensively interrogate the results using multiple analyses such as Mendelian randomization, functional assessment, co localization, genetic risk score, and pathway analyses. We identify a shared genetic component between urinary sodium and potassium expression and cardiovascular traits. Ingenuity pathway analysis shows that urinary sodium and potassium excretion loci are over-represented in behavioural response to stimuli. Our study highlights pathways that are shared between urinary sodium and potassium excretion and cardiovascular traits.

Genetic Similarity Assessment of Twin-Family Populations by Custom-Designed Genotyping Array

Twin registries often take part in large collaborative projects and are major contributors to genome-wide association (GWA) meta-analysis studies. In this article, we describe genotyping of twin-family populations from Australia, the Midwestern USA (Avera Twin Register), the Netherlands (Netherlands Twin Register), as well as a sample of mothers of twins from Nigeria to assess the extent, if any, of genetic differences between them. Genotyping in all cohorts was done using a custom-designed Illumina Global Screening Array (GSA), optimized to improve imputation quality for population-specific GWA studies. We investigated the degree of genetic similarity between the populations using several measures of population variation with genotype data generated from the GSA. Visualization of principal component analysis (PCA) revealed that the Australian, Dutch and Midwestern American populations exhibit negligible interpopulation stratification when compared to each other, to a reference European population and to globally distant populations. Estimations of fixation indices (FST values) between the Australian, Midwestern American and Netherlands populations suggest minimal genetic differentiation compared to the estimates between each population and a genetically distinct cohort (i.e., samples from Nigeria genotyped on GSA). Thus, results from this study demonstrate that genotype data from the Australian, Dutch and Midwestern American twin-family populations can be reasonably combined for joint-genetic analysis.

A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.

The role of DNA methylation and histone modifications in blood pressure: a systematic review

Epigenetic mechanisms might play a role in the pathophysiology of hypertension, a major risk factor for cardiovascular disease and renal failure. We aimed to systematically review studies investigating the association between epigenetic marks (global, candidate-gene or genome-wide methylation of DNA, and histone modifications) and blood pressure or hypertension. Five bibliographic databases were searched until the 7th of December 2018. Of 2984 identified references, 26 articles based on 25 unique studies met our inclusion criteria, which involved a total of 28,382 participants. The five studies that assessed global DNA methylation generally found lower methylation levels with higher systolic blood pressure, diastolic blood pressure, and/or presence of hypertension. Eighteen candidate-gene studies reported, in total, 16 differentially methylated genes, including renin-angiotensin-system-related genes (ACE promoter and AGTR1) and genes involved in sodium homeostasis and extracellular fluid volume maintenance system (NET promoter, SCNN1A, and ADD1). Between the three identified epigenome-wide association studies (EWAS), lower methylation levels of SULF1, EHMT2, and SKOR2 were found in hypertensive patients as compared with normotensive subjects, and lower methylation levels of PHGDH, SLC7A11, and TSPAN2 were associated with higher systolic and diastolic blood pressure. In summary, the most convincing evidence has been reported from candidate-gene studies, which show reproducible epigenetic changes in the interconnected renin-angiotensin and inflammatory systems. Our study highlights gaps in the literature on the role of histone modifications in blood pressure and the need to conduct high-quality studies, in particular, hypothesis-generating studies that may help to elucidate new molecular mechanisms.

Use of Genetic Variants Related to Antihypertensive Drugs to Inform on Efficacy and Side Effects

BACKGROUND

Drug effects can be investigated through natural variation in the genes for their protein targets. The present study aimed to use this approach to explore the potential side effects and repurposing potential of antihypertensive drugs, which are among the most commonly used medications worldwide.

METHODS

Genetic proxies for the effect of antihypertensive drug classes were identified as variants in the genes for the corresponding targets that associated with systolic blood pressure at genome-wide significance. Mendelian randomization estimates for drug effects on coronary heart disease and stroke risk were compared with randomized, controlled trial results. A phenome-wide association study in the UK Biobank was performed to identify potential side effects and repurposing opportunities, with findings investigated in the Vanderbilt University biobank (BioVU) and in observational analysis of the UK Biobank.

RESULTS

Suitable genetic proxies for angiotensin-converting enzyme inhibitors, β-blockers, and calcium channel blockers (CCBs) were identified. Mendelian randomization estimates for their effect on coronary heart disease and stroke risk, respectively, were comparable to results from randomized, controlled trials against placebo. A phenome-wide association study in the UK Biobank identified an association of the CCB standardized genetic risk score with increased risk of diverticulosis (odds ratio, 1.02 per standard deviation increase; 95% CI, 1.01-1.04), with a consistent estimate found in BioVU (odds ratio, 1.01; 95% CI, 1.00-1.02). Cox regression analysis of drug use in the UK Biobank suggested that this association was specific to nondihydropyridine CCBs (hazard ratio 1.49 considering thiazide diuretic agents as a comparator; 95% CI, 1.04-2.14) but not dihydropyridine CCBs (hazard ratio, 1.04; 95% CI, 0.83-1.32).

CONCLUSIONS

Genetic variants can be used to explore the efficacy and side effects of antihypertensive medications. The identified potential effect of nondihydropyridine CCBs on diverticulosis risk could have clinical implications and warrants further investigation.

ARMC 5 Variants and Risk of Hypertension in Blacks: MH- GRID Study

Background We recently found that ARMC 5 variants may be associated with primary aldosteronism in blacks. We investigated a cohort from the MH - GRID (Minority Health Genomics and Translational Research Bio-Repository Database) and tested the association between ARMC 5 variants and blood pressure in black s. Methods and Results Whole exome sequencing data of 1377 black s were analyzed. Target single-variant and gene-based association analyses of hypertension were performed for ARMC 5, and replicated in a subset of 3015 individuals of African descent from the UK Biobank cohort. Sixteen rare variants were significantly associated with hypertension ( P=0.0402) in the gene-based (optimized sequenced kernel association test) analysis; the 16 and one other, rs116201073, together, showed a strong association ( P=0.0003) with blood pressure in this data set. The presence of the rs116201073 variant was associated with lower blood pressure. We then used human embryonic kidney 293 and adrenocortical H295R cells transfected with an ARMC 5 construct containing rs116201073 (c.*920T>C). The latter was common in both the discovery ( MH - GRID ) and replication ( UK Biobank) data and reached statistical significance ( P=0.044 [odds ratio, 0.7] and P=0.007 [odds ratio, 0.76], respectively). The allele carrying rs116201073 increased levels of ARMC5 mRNA , consistent with its protective effect in the epidemiological data. Conclusions ARMC 5 shows an association with hypertension in black s when rare variants within the gene are considered. We also identified a protective variant of the ARMC 5 gene with an effect on ARMC 5 expression confirmed in vitro. These results extend our previous report of ARMC 5's possible involvement in the determination of blood pressure in blacks.

Integrative analysis of vascular endothelial cell genomic features identifies AIDA as a coronary artery disease candidate gene

BACKGROUND

Genome-wide association studies (GWAS) have identified hundreds of loci associated with coronary artery disease (CAD) and blood pressure (BP) or hypertension. Many of these loci are not linked to traditional risk factors, nor do they include obvious candidate genes, complicating their functional characterization. We hypothesize that many GWAS loci associated with vascular diseases modulate endothelial functions. Endothelial cells play critical roles in regulating vascular homeostasis, such as roles in forming a selective barrier, inflammation, hemostasis, and vascular tone, and endothelial dysfunction is a hallmark of atherosclerosis and hypertension. To test this hypothesis, we generate an integrated map of gene expression, open chromatin region, and 3D interactions in resting and TNFα-treated human endothelial cells.

RESULTS

We show that genetic variants associated with CAD and BP are enriched in open chromatin regions identified in endothelial cells. We identify physical loops by Hi-C and link open chromatin peaks that include CAD or BP SNPs with the promoters of genes expressed in endothelial cells. This analysis highlights 991 combinations of open chromatin regions and gene promoters that map to 38 CAD and 92 BP GWAS loci. We validate one CAD locus, by engineering a deletion of the TNFα-sensitive regulatory element using CRISPR/Cas9 and measure the effect on the expression of the novel CAD candidate gene AIDA.

CONCLUSIONS

Our data support an important role played by genetic variants acting in the vascular endothelium to modulate inter-individual risk in CAD and hypertension.

A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys

Defining cellular and molecular identities within the kidney is necessary to understand its organization and function in health and disease. Here we demonstrate a reproducible method with minimal artifacts for single-nucleus Droplet-based RNA sequencing (snDrop-Seq) that we use to resolve thirty distinct cell populations in human adult kidney. We define molecular transition states along more than ten nephron segments spanning two major kidney regions. We further delineate cell type-specific expression of genes associated with chronic kidney disease, diabetes and hypertension, providing insight into possible targeted therapies. This includes expression of a hypertension-associated mechano-sensory ion channel in mesangial cells, and identification of proximal tubule cell populations defined by pathogenic expression signatures. Our fully optimized, quality-controlled transcriptomic profiling pipeline constitutes a tool for the generation of healthy and diseased molecular atlases applicable to clinical samples.

Single-cell studies in solid tissues remain challenging and have benefited from the development of single-nuclei RNA sequencing strategies. Here Lake et al. apply single-nucleus RNA sequencing to human kidney tissues to provide a comprehensive molecular and cellular atlas of the human kidney, with potential implications for the understanding of kidney physiology and disease.

Long-Term Exposure to Elevated Systolic Blood Pressure in Predicting Incident Cardiovascular Disease: Evidence From Large-Scale Routine Electronic Health Records

Background How measures of long-term exposure to elevated blood pressure might add to the performance of "current" blood pressure in predicting future cardiovascular disease is unclear. We compared incident cardiovascular disease risk prediction using past, current, and usual systolic blood pressure alone or in combination. Methods and Results Using data from UK primary care linked electronic health records, we applied a landmark cohort study design and identified 80 964 people, aged 50 years (derivation cohort=64 772; validation cohort=16 192), who, at study entry, had recorded blood pressure, no prior cardiovascular disease, and no previous antihypertensive or lipid-lowering prescriptions. We used systolic blood pressure recorded up to 10 years before baseline to estimate past systolic blood pressure (mean, time-weighted mean, and variability) and usual systolic blood pressure (correcting current values for past time-dependent blood pressure fluctuations) and examined their prospective relation with incident cardiovascular disease (first hospitalization for or death from coronary heart disease or stroke/transient ischemic attack). We used Cox regression to estimate hazard ratios and applied Bayesian analysis within a machine learning framework in model development and validation. Predictive performance of models was assessed using discrimination (area under the receiver operating characteristic curve) and calibration metrics. We found that elevated past, current, and usual systolic blood pressure values were separately and independently associated with increased incident cardiovascular disease risk. When used alone, the hazard ratio (95% credible interval) per 20-mm Hg increase in current systolic blood pressure was 1.22 (1.18-1.30), but associations were stronger for past systolic blood pressure (mean and time-weighted mean) and usual systolic blood pressure (hazard ratio ranging from 1.39-1.45). The area under the receiver operating characteristic curve for a model that included current systolic blood pressure, sex, smoking, deprivation, diabetes mellitus, and lipid profile was 0.747 (95% credible interval, 0.722-0.811). The addition of past systolic blood pressure mean, time-weighted mean, or variability to this model increased the area under the receiver operating characteristic curve (95% credible interval) to 0.750 (0.727-0.811), 0.750 (0.726-0.811), and 0.748 (0.723-0.811), respectively, with all models showing good calibration. Similar small improvements in area under the receiver operating characteristic curve were observed when testing models on the validation cohort, in sex-stratified analyses, or by using different landmark ages (40 or 60 years). Conclusions Using multiple blood pressure recordings from patients' electronic health records showed stronger associations with incident cardiovascular disease than a single blood pressure measurement, but their addition to multivariate risk prediction models had negligible effects on model performance.

A polymorphism in intron I of the human angiotensinogen gene (hAGT) affects binding by HNF3 and hAGT expression and increases blood pressure in mice

Angiotensinogen (AGT) is the precursor of one of the most potent vasoconstrictors, peptide angiotensin II. Genome-wide association studies have shown that two A/G polymorphisms (rs2493134 and rs2004776), located at +507 and +1164 in intron I of the human AGT (hAGT) gene, are associated with hypertension. Polymorphisms of the AGT gene result in two main haplotypes. Hap-I contains the variants -217A, -6A, +507G, and +1164A and is pro-hypertensive, whereas Hap-II contains the variants -217G, -6G, +507A, and +1164G and does not affect blood pressure. The nucleotide sequence of intron I of the hAGT gene containing the +1164A variant has a stronger homology with the hepatocyte nuclear factor 3 (HNF3)-binding site than +1164G. Here we found that an oligonucleotide containing +1164A binds HNF3β more strongly than +1164G and that Hap-I-containing reporter gene constructs have increased basal and HNF3- and glucocorticoid-induced promoter activity in transiently transfected liver and kidney cells. Using a knock-in approach at the hypoxanthine-guanine phosphoribosyltransferase locus, we generated a transgenic mouse model containing the human renin (hREN) gene and either Hap-I or Hap-II. We show that transgenic animals containing Hap-I have increased blood pressure compared with those containing Hap-II. Moreover, the transcription factors glucocorticoid receptor, CCAAT enhancer-binding protein β, and HNF3β bound more strongly to chromatin obtained from the liver of transgenic animals containing Hap-I than to liver chromatin from Hap-II-containing animals. These findings suggest that, unlike Hap-II variants, Hap-I variants of the hAGT gene have increased transcription rates, resulting in elevated blood pressure.